The Geometry of ATG-Walks of the Omicron SARS CoV-2 Virus RNAs

Kouzaev, Guennadi A.

doi:10.1101/2021.12.20.473613

Cited by 2 publications

(4 citation statements)

References 10 publications

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“…For instance, the divergence of these curves estimated at 29000 i x = is around only 1%. This confirms the conclusions of many specialists that no new recombined strains have appeared up to this moment, despite many mutations found to date, including the last Omicron lineage [68].…”

Section: Study Of Atg-walks Of the Complete Genome Sequences Of The Sars Cov-2 Virussupporting

confidence: 88%

“…is around only 1%. This confirms the conclusions of many specialists that no new recombined strains have appeared up to this moment, despite many mutations found to date, including the last Omicron lineage [68]. It means that the virus is rather resistant or stable towards forming new families with distinctive properties.…”

Section: Study Of Atg-walks Of the Complete Genome Sequences Of The S...supporting

confidence: 86%

“…In some studied samples (here, and in Refs. [42], [68]), perturbations are near the end of the orf1ab gene, as is seen using a graphical tool of GenBank [39]. Perturbations were detected by calculating the i x coordinates according to known i y .…”

Section: The Ordinate Axis Xmentioning

confidence: 99%

“…7 and Refs. [42], [68]). The origin of this is unknown, but it was not coupled with the lineages of viruses and their clades.…”

Section: The Ordinate Axis Xmentioning

confidence: 99%

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Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

Belinsky¹,

Kouzaev

2021

Preprint

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The worldwide spread of SARS-CoV-2 virus increases interest in the research of virus genomics and the creation of more advanced study methods. This work aims to develop a new fast DNA walk algorithm for one-dimensional visualization of RNAs based on a big-data method and comparative examination of several viruses and their lines and strains. In this work, a new metric-based algorithm for quantitative and visual analyses of RNAs is proposed and considered. It allows finding any fragments of genomic sequences using the Hamming distance between the binary-expressed RNA characters and symbols of a fragment under the search and building one-dimensional trajectories of genomic walks convenient for quantitative and qualitative analyses of RNAs and DNAs. Similarly, human-language texts can be processed and compared with genomic sequences.This algorithm is used to investigate the complete genomic sequences of SARS CoV-2, MERS, Dengue, and Ebola viruses available from Genbank and GISAID databases. The distributions of atg codon-starting triplets along with these sequences are built and considered as their atg-schemes. Additionally to the atg-walks, single-symbols distributions are calculated to detect the codon-content mutations, which do not change the atg-triplet coordinates along with genomic sequences. The visual analyses of distributions consisting of several hundred triplets enable us to define the level of stability of RNAs towards essential mutations and perform their classing. Statistical studies are applied to distributions of the inter-atg and inter-symbol distances along with genomic sequences. The fractal dimension values of these distributions are calculated, enabling them to correspond to the mutations discovered by Hamming walks and fractal-dimension values of several ten virus samples investigated here. The developed metric-based-based algorithm allows building one-dimensional RNA schemes of different scale levels and effectively analyzing the virus mutations with their classing.

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Section: Study Of Atg-walks Of the Complete Genome Sequences Of The Sars Cov-2 Virussupporting

confidence: 88%

Section: Study Of Atg-walks Of the Complete Genome Sequences Of The S...supporting

confidence: 86%

Section: The Ordinate Axis Xmentioning

confidence: 99%

“…7 and Refs. [42], [68]). The origin of this is unknown, but it was not coupled with the lineages of viruses and their clades.…”

Section: The Ordinate Axis Xmentioning

confidence: 99%

See 2 more Smart Citations

Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

Belinsky¹,

Kouzaev

2021

Preprint

Self Cite

View full text Add to dashboard Cite

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Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

Belinsky¹,

Kouzaev

2022

Wseas Transactions on Circuits and Systems

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This work aims to study the virus RNAs using a novel accelerated algorithm to explore any-length repetitive genomic fragments in sequences using Hamming distance between the binary-expressed characters of an RNA and a query pattern. Primary attention is paid to the building and analyzing 1-D distributions (walks) of atg-patterns - codon-starting triplets in genomes. These triplets compose a distributed set called a word scheme of RNA. A complete genome map is built by plotting the mentioned atg-walks, trajectories of separate (a-, c-, g-, and t-symbols) nucleotides, and the lines designating the genomic words. The said map can be additionally equipped by gene’s designations making this tool pertinent for multi-scale genomic analyses. The visual examination of atg-walks is followed by calculating statistical parameters of genomic sequences, including estimating walk- geometry deviation of RNAs and fractal properties of word-length distributions. This approach is applied to the SARS CoV-2, MERS CoV, Dengue, and Ebola viruses, whose complete genomic sequences are taken from GenBank and GISAID. The relative stability of these walks for SARS CoV-2 and MERS CoV viruses was found, unlike the Dengue and Ebola distributions that showed an increased deviation of their geometrical and fractal characteristics. The developed approach can be useful in further studying mutations of viruses and building their phylogenic trees.

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The Geometry of ATG-Walks of the Omicron SARS CoV-2 Virus RNAs

Cited by 2 publications

References 10 publications

Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

Visual and Quantitative Analyses of Virus Genomic Sequences using a Metric-based Algorithm

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